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DHARMa vs itp

A side-by-side editorial comparison of DHARMa and itp — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

DHARMa vs itp: at a glance

FeatureDHARMaitp
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesresidual-diagnostics, glmm, breaking-change, bayesiannumerical-methods, root-finding, rcpp, cran-maintenance
Last editorial update1h ago15m ago
WebsiteVisit →Visit →

What is DHARMa?

DHARMa changed how GLMM residuals are simulated, so the same code now returns different numbers.

DHARMa generates scaled quantile residuals for fitted GLMMs and runs the dispersion, uniformity, and autocorrelation tests built on them. Version 0.5.0 changed the default simulation for hierarchical models from the model's own default, mostly unconditional, to conditional simulation, and states plainly that residuals will differ from those computed by older versions. The same release added brms to the supported model set and reworked how predictors are passed to plotting and testing functions.

Read the full DHARMa trajectory →

What is itp?

A single-algorithm root-finder that finished its job in 2022 and has been idling since

itp implements one thing: the Interpolate, Truncate, Project root-finding algorithm of Oliveira and Takahashi, which narrows a bracketing interval each iteration and keeps bisection's worst-case guarantee while converging faster on well-behaved functions. The package reached its intended shape within about six weeks of first release, gaining a C++ entry point and the ability to take C++ function pointers. Everything after mid-2022 is compiler and CRAN upkeep.

Read the full itp trajectory →

DHARMa vs itp: editorial side-by-side

D
DHARMa
ANALYTICS
0.0

DHARMa changed how GLMM residuals are simulated, so the same code now returns different numbers.

◆ Current state

DHARMa generates scaled quantile residuals for fitted GLMMs and runs the dispersion, uniformity, and autocorrelation tests built on them. Version 0.5.0 changed the default simulation for hierarchical models from the model's own default, mostly unconditional, to conditional simulation, and states plainly that residuals will differ from those computed by older versions. The same release added brms to the supported model set and reworked how predictors are passed to plotting and testing functions.

◆ Where it's heading

The package has spent several releases widening which model backends it can diagnose, from glmmTMB through mgcv, phylolm and now brms, while methodological work has gone into handling correlated residuals via the rotation argument. Version 0.5.0 shifts from adding coverage to changing defaults for statistical power. The formula interface arriving across plotResiduals, testCategorical, testQuantiles and the autocorrelation tests suggests the API is being unified rather than extended function by function.

◆ Prediction

The next releases will likely broaden brms support past the simple-model restriction and continue converting remaining functions to the formula interface.

I
itp
ANALYTICS
0.0

A single-algorithm root-finder that finished its job in 2022 and has been idling since

◆ Current state

itp implements one thing: the Interpolate, Truncate, Project root-finding algorithm of Oliveira and Takahashi, which narrows a bracketing interval each iteration and keeps bisection's worst-case guarantee while converging faster on well-behaved functions. The package reached its intended shape within about six weeks of first release, gaining a C++ entry point and the ability to take C++ function pointers. Everything after mid-2022 is compiler and CRAN upkeep.

◆ Where it's heading

The arc is short and complete. Three releases in June and July 2022 took the package from an R implementation to one that can run the whole algorithm in C++ and accept user-supplied C++ functions via Rcpp's external pointer framework. Since then the only releases have been reactions to Rcpp changes that would otherwise trip CRAN checks — 2023 and 2026, both traceable to specific upstream Rcpp issues.

◆ Prediction

There is no visible development agenda here; the entries suggest the package surfaces only when Rcpp or CRAN check policy forces a patch.

Alternatives to DHARMa and itp

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either DHARMa or itp.

See all DHARMa alternatives → · See all itp alternatives →

Recent activity from DHARMa and itp

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 2mo agoDHARMaConditional simulation becomes the GLMM default, changing residuals
  2. 7mo agoitpRcpp Rf_error masking patch, README and help-file typo
  3. 1y agoDHARMaDHARMa 0.4.7
  4. 2y agoitpRcpp fix clears CRAN check warnings
  5. 3y agoDHARMaDHARMa 0.4.6
  6. 4y agoitpitp_c runs the whole algorithm in C++
  7. 4y agoitpAccepts C++ function pointers, adds a plot method
  8. 4y agoitpBracketing interval fix for locally decreasing functions
  9. 4y agoitpFirst release of the ITP root-finding algorithm
  10. 4y agoDHARMaDHARMa 0.4.5
  11. 4y agoDHARMaDHARMa 0.4.4
  12. 5y agoDHARMaDHARMa 0.4.3

Frequently asked questions

What is the difference between DHARMa and itp?

Both compete on the same themes — r-package — within Analytics. DHARMa and itp are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is DHARMa better than itp?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. DHARMa and itp are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to DHARMa?

Top DHARMa alternatives in Analytics are ranked by recent ship velocity. Browse the "DHARMa alternatives" section above for the current picks, or visit /alternatives/dharma for the full list with editorial commentary on each.

What are the best alternatives to itp?

Top itp alternatives in Analytics are ranked by recent ship velocity. Browse the "itp alternatives" section above for the current picks, or visit /alternatives/itp for the full list with editorial commentary on each.